Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

被引：6

作者：

Zhang Yankun & Liu Chongqing Institute of Image Processing and Pattern Recognition

机构：

来源：

JournalofSystemsEngineeringandElectronics | 2003年 / 03期

关键词：

Face recognition; Support vector machine; Nearest neighbor classifier; Principal component analysis;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-

引用

页码：73 / 76

页数：4